Design and build scalable machine learning infrastructure, enabling data scientists to develop, deploy, and monitor production ML models. Focus on experimentation, training, deployment, inference, monitoring, and retraining. Collaborate with cross-functional teams to support underwriting systems and define model interfaces.
Key Highlights
Key Responsibilities
Technical Skills Required
Benefits & Perks
Nice to Have
Job Description
🚀 Senior Software Engineer, ML Platform | Parafin
📍 San Francisco, CA (Hybrid)
💰 $230K+Base with Competitive Equity
🛂 Visa Sponsorship Available (H-1B Transfers & O-1)
Parafin is seeking a Senior Software Engineer, ML Platform to own and scale the infrastructure powering machine learning-driven underwriting and financial products. This is a unique opportunity to build a critical ML platform from the ground up, enabling Data Scientists to efficiently develop, deploy, monitor, and scale production ML models that directly impact small businesses across partner ecosystems including Amazon, DoorDash, Walmart, and TikTok
.What You'll D
o🔹 Architect and build the next generation ML Platform supporting experimentation, training, deployment, inference, monitoring, and retraining
.🔹 Transform data science workflows into production-grade software by building reusable libraries, pipelines, frameworks, SDKs, CLIs, templates, and developer tooling
.🔹 Design and scale real-time inference infrastructure, ensuring low latency, reliability, and high availability
.🔹 Expand and optimize large-scale batch inference systems, focusing on scheduling, observability, cost optimization, rollback capabilities, and operational excellence
.🔹 Own and evolve the feature store ecosystem, including offline and online feature management, point-in-time correctness, high-throughput access patterns, and feature governance
.🔹 Drive platform reliability through monitoring, alerting, dashboards, incident response, model performance tracking, drift detection, data quality validation, and infrastructure observability
.🔹 Partner closely with Data Science, Infrastructure, and Product teams to support underwriting systems, define model interfaces, establish SLAs, and implement production safeguards
.Required Qualification
s✔ 5+ years of Software Engineering experience, including ML Platform, MLOps, Data Infrastructure, or Machine Learning Engineering environments
.✔ Strong software engineering fundamentals with expertise in
- :Pytho
- nSQ
- LSoftware architecture & desig
- nTesting and code qualit
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y✔ Hands-on experience with
- :Spark / PySpar
- kDatabrick
- sMLflo
- wAirflow (or equivalent orchestration tools
- )AWS Cloud Service
s✔ Experience building
- :Feature Store
- sModel Registrie
- sML Deployment Pipeline
- sReal-Time Inference System
- sLarge-Scale Data Processing Platform
- sBatch and Streaming Data Architecture
s✔ Strong understanding of
- :ML lifecycle managemen
- tModel evaluation & validatio
- nFeature engineerin
- gDrift monitorin
- gExperiment trackin
- gProduction ML best practice
- sProbability & Statistics fundamental
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s✔ Proven ability to build scalable platforms that enable Data Scientists and ML Engineers to operate efficiently at scale
.Preferred Qualification
s⭐ Experience with
- :Kafka or Kinesi
- sFeast, Tecton, or similar Feature Store technologie
- sDatabricks Model Servin
- gLow-latency model serving architecture
- sA/B testing platform
- sShadow deployment
- sCanary release
- sAutomated rollback framework
s⭐ Domain expertise in
- :FinTec
- hLendin
- gCredit Ris
- kUnderwritin
- gRisk Modelin
- gFinancial Service
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s⭐ Previous experience in startup or high-growth environments where you've built systems from the ground up and influenced technical strategy
.Ideal Candidat
eWe're looking for an engineer who thinks beyond model development and focuses on building the infrastructure that makes ML teams successful. The ideal candidate has built reusable, scalable, software-engineering-grade platforms that empower data scientists to ship models safely and efficiently into production
.You'll thrive in this role if you enjoy solving platform-scale challenges, influencing architectural direction, working in fast-paced environments, and taking ownership of mission-critical systems. Experience supporting high-volume ML workloads and enabling cross-functional teams is highly valued
.Why Join Parafin
?✅ Ground-floor ownership of a critical ML Platform initiativ
e✅ Direct impact on financial products serving millions of users through leading technology platform
s✅ Opportunity to shape company-wide ML architecture and infrastructure strateg
y✅ Backed by top-tier investors with over $194M raise
d✅ High-growth environment with significant investment in platform modernization and scalabilit
y✅ Competitive compensation, equity participation, and visa sponsorship suppor
t✅ Work alongside exceptional engineers, data scientists, and infrastructure leaders solving complex real-world challenges
.Tech Stac
kPython | SQL | Spark | PySpark | Databricks | MLflow | Airflow | AWS | Snowflake | Kafka | Kinesis | Feature Stores | Real-Time Inference | MLOps Platform
s📩 If you're passionate about building world-class ML infrastructure and enabling machine learning at scale, we'd love to hear from you
.#Hiring #SeniorSoftwareEngineer #MLPlatform #MLOps #MachineLearningEngineering #Python #Spark #PySpark #Databricks #MLflow #AWS #Kafka #FeatureStore #DataEngineering #FinTech #InfrastructureEngineering #SoftwareEngineering #AIJobs #TechHiring #SanFranciscoJobs #MachineLearningInfrastructure #DistributedSystems #PlatformEngineering #HiringNo
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